A distributed data-mining
software platform for
EXTReme dAta Across the
Compute conTinuum

Delivering a data-driven open-source platform integrating cloud, edge and HPC technologies for trustworthy, accurate, fair and green data mining workflows for high-quality actionable knowledge

Objectives

Enable the development of complex and secure data mining workflows

Develop novel data-driven orchestration mechanisms to efficiently deploy and execute data mining workflows

Deliver the EXTRACT software platform and demonstrate its benefits in two use cases

Fully exploit the performance capabilities of the compute continuum to effectively address extreme data characteristics (high volume, variety, velocity, veracity)  holistically

Foster the adoption of EXTRACT technology by industrial and academic communitie

Use cases

Personalized Evacuation Routing (PER) System

A Personalized Evacuation Routing (PER) System will serve to guide citizens in an urban environment (the city of Venice) through a safe route in real time.

The EXTRACT platform will be used to develop, deploy and execute a data-mining workflow to generate personalized evacuation routes for each citizen, displayed in a mobile phone app, by processing and analysing extreme data composed of Copernicus and Galileo satellite data, IoT sensors installed across the city, 5G mobile signal, and a semantic data lake fusing all this information.

Transient Astrophysics with a Square Kilometer Array Pathfinder  (TASKA)

The Transient Astrophysics with a Square Kilometer Array Pathfinder (TASKA) case will use EXTRACT technology to develop data mining workflows that effectively reduce the huge amount of raw data produced by NenuFAR radio-telescopes by a factor of 100. This will allow the populating of high-quality datasets that will be openly accessible to the astronomy community (through the EOSC portal) to be leveraged for multiple research activities.

CompContinuum Workshop at HiPEAC 2024

CompContinuum Workshop at HiPEAC 2024

Figure 1: Xavier Palomo, from partner BSC, shares EXTRACT use cases to demonstrate potential crisis management applications of an efficient compute continuum The half day workshop, "CompContinuum: Computing Continuum of Cloud, Edge, and IoT Technologies” held on the...

Serving Models at Scale in EXTRACT

Serving Models at Scale in EXTRACT

A machine-learning (ML) model recommends where each individual should go in case of a disaster, taking into account the person’s characteristics and capabilities (age, disability, etc) and the limited capacity and labyrinthian streets and alleys of ancient Venice. To allow people’s devices to access this model, it needs to be served, i.e., be available as a remote service.

AMLE SUMMER SCHOOL

AMLE SUMMER SCHOOL

EXTRACT Coordinator, Eduardo Quiñones gave the keynote speech at the 2023 Adaptive Machine Learning at the Network Edge (AMLE) Summer School. His speech, entitled "Task-based Parallel Programming Models: The Convergence of High-Performance and Edge Computing Domains",...

Presentation in mobility course

Presentation in mobility course

EXTRACT project coordinator, Dr. Eduardo Quiñones, presented in the course "La Digitalizació de La Mobilitat" hosted by mobility consultancy, FACTUAL, based in Barcelona. The course took place in Barcelona from 10-11 July 2023 and focused on new technologies in the...